Gen AI Developer (Contract)

Role Overview

Design, develop, and maintain scalable Gen AI applications using LLMs, RAG, and agent-based architectures. This role involves building end-to-end AI solutions, from RAG pipelines to intelligent AI agents, ensuring they are production-ready, secure, and scalable.

Responsibilities

• Design, develop, and maintain scalable Gen AI applications using LLMs, RAG, and agent-based architectures.
• Develop and optimize backend APIs and microservices using Python and relevant frameworks.
• Build end-to-end RAG pipelines, including document ingestion, preprocessing, chunking, embeddings, retrieval, and indexing.
• Work with vector databases for efficient semantic search and context retrieval.
• Develop LLM applications using LangChain, LangGraph, and LangFuse.
• Implement and deploy LLM solutions using Amazon Bedrock and integrate foundation models into enterprise applications.
• Design intelligent AI agents, including tool calling, workflow orchestration, memory, and multi-step reasoning patterns.
• Develop effective system prompts and context-engineering strategies to improve accuracy, relevance, and reliability of Gen AI applications.
• Implement SSO-based authentication and authorization for enterprise Gen AI applications.
• Containerize applications and services using Docker and support scalable deployment across enterprise environments.
• Implement observability and monitoring for APIs, LLM applications, model performance, latency, failures, and usage.
• Optimize applications for performance, scalability, reliability, security, and cost efficiency.
• Collaborate with architects, data engineers, product teams, and business stakeholders to translate requirements into production-ready AI solutions.
• Follow best practices for Gen AI security, data privacy, prompt management, evaluation, and responsible AI.
• Troubleshoot production issues and continuously enhance the quality and performance of deployed Gen AI applications.

Requirements

• Proven experience in building and deploying Gen AI and LLM based applications.
• Strong proficiency in Python and backend development.
• Experience with RAG architectures and vector databases.
• Hands-on experience with LangChain or similar orchestration frameworks.
• Familiarity with cloud-based AI services like Amazon Bedrock.
• Knowledge of containerization using Docker.

Skills

• Python
• LangChain
• Amazon Bedrock
• Docker
• Vector Databases